E-PINN: extended physics informed neural network for the forward and inverse problems of high-order nonlinear integro-differential equations
Author:
Affiliation:
1. Department of Mathematics, School of Science, Hangzhou Dianzi University, Hangzhou, China
Funder
Natural Science Foundation of Zhejiang Province
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/00207160.2024.2374820
Reference29 articles.
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3. On exact computation with an infinitely wide neural net;Arora S.;Adv. Neural. Inf. Process. Syst.,2019
4. Study of Fractional Order Integro-Differential Equations by using Chebyshev Neural Network
5. Integro-differential equations for option prices in exponential Lévy models
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